Wind power is considered one of the cleanest, most environmentally friendly energy sources presently available, and wind turbines have gained increased attention in this regard. A modern wind turbine typically includes a tower, a generator, a gearbox, a nacelle, and one or more rotor blades. The rotor blades capture kinetic energy from wind using known foil principles and transmit the kinetic energy through rotational energy to turn a shaft coupling the rotor blades to a gearbox, or if a gearbox is not used, directly to the generator. The generator then converts the mechanical energy to electrical energy that may be deployed to a utility grid.
High wind speeds are critical for wind turbines and allow the wind turbine to generate power. At certain high wind speeds (i.e. a cut out wind speed), however, a control strategy must be implemented to maintain the loads of the wind turbine within the design load envelope for each of the wind turbine components. Thus, many control technologies shut down the wind turbine above the cut out wind speed to protect the various components. Though this strategy prevents damaging loads that might occur due to the higher turbulence in the wind, the lack of energy capture in the region above cut out wind speed is a disadvantage. Also, a brief increase in wind speed might trigger a turbine shutdown, while the recovery to normal power production may take some time. On the same token, the occurrence of high turbulence at rated wind speeds will also increase the likelihood of triggering a turbine shutdown.
Accordingly, an improved system and method for controlling a wind turbine that addresses the aforementioned issues above would be advantageous. More specifically, a system and method that utilizes a statistical approach for determining a reduction in the power output of the wind turbine based on a function of a number and type of detected adverse wind conditions occurring during a certain time period would be desired.